Collaborative Research: System Optimization and Data Analysis in Two-Dimensional Liquid Chromatography

合作研究：二维液相色谱系统优化和数据分析

• 批准号: 1213244
• 负责人: Dwight Stoll
• 金额: $ 5.1万
• 依托单位: Gustavus Adolphus College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-15 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1213244&HistoricalAwards=false
• 关键词: Collaborative; Research; System; Optimization; Data

With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor Sarah Rutan at Virginia Commonwealth University, Professor Peter Carr at University of Minnesota, Professor Dwight Stoll at Gustavus Adolphus College and their groups will address the challenges of performing quantitative comprehensive two dimensional liquid chromatography (LCxLC). This technique carries out separations of the component molecules present in complex mixtures using two very different liquid separation systems, and offers a more powerful method for separating complex mixtures such as urine. The proposed research will enable LCxLC to become a practical technique for the analysis of small molecule metabolites, which will therefore lead to more rapid and facile discovery of molecular markers of disease and treatment. The intellectual merit of the work carried out by this team of investigators lies in the development of a fundamental understanding of how changes in the chemistry of the chromatographic separation processes affect the characteristics of the resulting data, developing an understanding how these chemical factors affect the performance of the data analysis methods, and tuning the data analysis methods to adapt to these data features. These efforts will transform a time-consuming process that is at best semi-quantitative, into a rapid and efficient method that will provide precise, quantitative results for biomarker identification.The broader impacts of the work lie in providing biological scientists with the tools needed to characterize the amounts and relationships of various molecular players as they vary depending on growth, disease state and environmental exposure. This research will contribute towards reaching a holistic understanding of complex biological systems. This knowledge will contribute to refined technologies that have tremendous promise for understanding and curing diseases, enhancing agriculture and preserving the environment. In order to make chromatographic concepts more accessible to students, a series of dynamic, online homework problems will be developed based on online LC simulators. There is also a strong component of human resources development in the training of graduate and undergraduate students, and post-doctoral scholars for careers in chemistry and biology. The students working on this project will benefit from the synergy of working with three talented and creative researchers in separation science.

在化学系化学测量和成像项目的支持下，弗吉尼亚联邦大学的Sarah Rutan教授、明尼苏达大学的Peter卡尔教授、古斯塔夫斯·阿道夫学院的德怀特·斯托尔教授及其团队将解决进行定量的挑战。全面二维液相色谱（LCxLC）。该技术使用两种非常不同的液体分离系统对复杂混合物中存在的组分分子进行分离，并提供了一种更有效的分离复杂混合物（如尿液）的方法。拟议的研究将使LCxLC成为一种分析小分子代谢物的实用技术，因此将导致更快速，更容易地发现疾病和治疗的分子标志物。该研究团队开展的工作的智力价值在于对色谱分离过程的化学变化如何影响所得数据的特征的基本理解，了解这些化学因素如何影响数据分析方法的性能，并调整数据分析方法以适应这些数据特征。这些努力将把一个耗时的过程，最多是半定量的，变成一个快速和有效的方法，将提供精确的，定量的结果，生物标志物identifiation.The更广泛的影响，工作在于提供生物科学家所需的工具来表征的数量和各种分子球员的关系，因为它们取决于生长，疾病状态和环境暴露。这项研究将有助于全面了解复杂的生物系统。 这些知识将有助于改进技术，这些技术在理解和治疗疾病、加强农业和保护环境方面具有巨大的前景。为了使色谱的概念更容易为学生，一系列的动态，在线作业的问题将开发基于在线LC模拟器。在培养研究生和本科生以及从事化学和生物学职业的博士后学者方面，人力资源开发也是一个重要组成部分。从事该项目的学生将受益于与三位有才华和创造力的分离科学研究人员合作的协同作用。